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Journal articles on the topic 'Urban planning; Traffic control'
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Ivankovic, Franc, Mauro Vallati, Lukáš Chrpa, and Marco Roveri. "Urban Traffic Control via Planning with Global State Constraints (Extended Abstract)." Proceedings of the International Symposium on Combinatorial Search 15, no. 1 (July 17, 2022): 291–93. http://dx.doi.org/10.1609/socs.v15i1.21789.
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Planning with global state constraints is an extension of classical planning such that some properties of each state are derived via a set of rules common to all states. This approach is important for the application of planning techniques in manipulating cyber-physical systems, and has been shown to be effective in practice. Urban Traffic Control (UTC) deals with the control and management of traffic in urban regions, and includes the optimisation of traffic signals configuration to minimise traffic congestion and travel delays. In this paper, we briefly introduce how to cast the UTC problem into the formalism of planning with global state constraints, and we perform a preliminary experimental evaluation considering significant scenarios taken from the literature, and a new one based on real-world data. The results show that the approach is feasible, and the quality of generated solutions has been confirmed in simulation using existing symbolic models.
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Laing, Richard, Amar Bennadji, and David Gray. "Traffic Control and CO2 Reduction." International Journal of E-Planning Research 2, no. 1 (January 2013): 43–57. http://dx.doi.org/10.4018/ijepr.2013010103.
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The aim of the research described in this article was to explore the use of intelligent virtual transport modelling, within the context of a case study involving the development of a University estate. Through the application of visualisation techniques, the study was able to explore how such techniques can lead to enlightenment of potential solutions, whilst simultaneously demonstrating the effects of design solutions on CO2 emissions. The research used UC-win/Road software to support the visualisation component. The software supports the integration of road planning within urban settings and enables the creation of walkthrough visualisations, useful in communication with non-specialist end users. Outcomes of the research included an animation to assist planners in the consideration of travel time, distance and staff experience. Vitally, though, this is intrinsically connected with a study of how one can ensure that visual elements of a design process are undertaken to support complex technical, social and environmental decision making. The work is placed within a consideration of participation in the planning and design of sustainable transport approaches in urban areas, and the approach described should be viewed within this context.
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Smith, Stephen. "Smart Infrastructure for Future Urban Mobility." AI Magazine 41, no. 1 (April 13, 2020): 5–18. http://dx.doi.org/10.1609/aimag.v41i1.5290.
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Real-time traffic signal control presents a challenging multiagent planning problem, particularly in urban road networks where, unlike simpler arterial settings, there are competing dominant traffic flows that shift through the day. Further complicating matters, urban environments require attention to multimodal traffic flows (vehicles, pedestrians, bicyclists, buses) that move at different speeds and may be given different priorities. For the past several years, my research group has been developing and refining a real-time, adaptive traffic signal control system to address these challenges, referred to as scalable urban traffic control (Surtrac). Combining principles from automated planning and scheduling, multiagent systems, and traffic theory, Surtrac treats traffic signal control as a decentralized online planning process. In operation, each intersection repeatedly generates and executes (in rolling horizon fashion) signal-timing plans that optimize the movement of currently sensed approaching traffic through the intersection. Each time a new plan is produced (nominally every couple of seconds), the intersection communicates to its downstream neighbors what traffic it expects to send their way, allowing intersections to construct longer horizon plans and achieve coordinated behavior. Initial evaluation of Surtrac in the field has demonstrated significant performance improvements, and the technology is now deployed and operating in several U.S. cities. More recent work has focused on integrating real-time adaptive signal control with emerging connected vehicle technology, and exploration of the opportunities for enhanced mobility that direct vehicle (or pedestrian) to infrastructure communication can provide. Current technology development efforts center on vehicle route sharing, smart transit priority, safe intersection crossing for pedestrians with disabilities, real-time incident detection, and integrated optimization of signal control and route choice decisions. This article provides an overview of this overall research effort.
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McCluskey, Thomas, and Mauro Vallati. "Embedding Automated Planning within Urban Traffic Management Operations." Proceedings of the International Conference on Automated Planning and Scheduling 27 (June 5, 2017): 391–99. http://dx.doi.org/10.1609/icaps.v27i1.13842.
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This paper is an experience report on the results of an industry-led collaborative project aimed at automating the control of traffic flow within a large city centre. A major focus of the automation was to deal with abnormal or unexpected events such as roadworks, road closures or excessive demand, resulting in periods of saturation of the network within some region of the city. We describe the resulting system which works by sourcing and semantically enriching urban traffic data, and uses the derived knowledge as input to an automated planning component to generate light signal control strategies in real time. This paper reports on the development surrounding the planning component, and in particular the engineering, configuration and validation issues that arose in the application. It discusses a range of lessons learned from the experience of deploying automated planning in the road transport area, under the direction of transport operators and technology developers.
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Carlier, Guillaume, and Filippo Santambrogio. "A variational model for urban planning with traffic congestion." ESAIM: Control, Optimisation and Calculus of Variations 11, no. 4 (September 15, 2005): 595–613. http://dx.doi.org/10.1051/cocv:2005022.
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Song, Jiaxun, Qi Meng, and Jian Kang. "A traffic big data analysis on relationships between urban planning and traffic noise level--taking Dongguan Demonstration Area, China as an example." INTER-NOISE and NOISE-CON Congress and Conference Proceedings 265, no. 7 (February 1, 2023): 784–94. http://dx.doi.org/10.3397/in_2022_0110.
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With the promotion of smart city research, traffic big data has become a new way to study urban traffic noise. Taking Dongguan Demonstration Area, China as an example, this research discussed the relationships between traffic noise levels and urban plannings using geographic information scienceGIS, global positioning system (GPS) techniques and OpenITS Organization OpenData. The results showed that, for the whole area, some planning factors, say global integration, local integration (R=500m), global betweenness, local betweenness (R=500m) and number of points of interest (POIs) had significant positive correlations with the daytime traffic noise levels. Among them, the number of POIs had the strongest correlation with the traffic noise levels (r=0.560 p<0.01). However, the degree of influence of each variable on traffic noise levels can be changed with geographical locations. This research also identified specific areas where traffic noise levels were negatively correlated with local integration and local betweenness, which had great potential to provide a recreational and peaceful place for people to walk. Therefore, the urban areas' centers and fringes can be studied separately to effectively control traffic noise by changing the urban plannings.
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Wang, Dan Ping, and Kun Yuan Hu. "Research on Path Optimization of Urban Traffic Guidance System." Applied Mechanics and Materials 624 (August 2014): 520–23. http://dx.doi.org/10.4028/www.scientific.net/amm.624.520.
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With the rapid development of economics and technology; the number of vehicles has largely increased. In this paper, traffic guidance and traffic control systems were researched as well as the Internet of Things (IOT). The author tried to combine these three parts to send traffic data to road users so as to let them choose the best route to travel. Meanwhile, traffic network optimization has been realized to reduce traffic congestion areas. This paper has optimized regional traffic signal control systems based on IOT, traffic guidance as well as traffic assignment, involved data sources, IOT design patterns, data collection as well as the relationship between guidance obeisance rate and traffic jam. It also involved the definition of ideal traffic shortest routes, planning and designing of traffic control systems. Results and researches could hope to combine with reality in order to reduce traffic congestion.
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WU, WEI. "Research on Urban Congestion Control Strategy Based on Smart Traffic Management System." Journal of Humanities and Social Sciences Studies 4, no. 1 (February 14, 2022): 89–96. http://dx.doi.org/10.32996/jhsss.2022.4.1.9.
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With the rapid economic development, the scale of cities has expanded, the population of cities has increased, the number of motor vehicles has increased, the contradiction between traffic supply and traffic demand has increased, and traffic congestion has appeared in major cities. Many countries have proposed planning and construction measures and policies in the current smart transportation development and construction. The construction of smart transportation requires a complete management system for planning. The article selects smart transportation in some countries and regions to conduct inductive analysis in the smart transportation management system construction measures and put forward suggestions for my country's smart transportation construction to effectively alleviate urban congestion.
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Jiang, Di Gang, and Yi Zhou Wu. "A Planning Method of Urban Non-Motorized Traffic System — A Case from Hangzhou." Applied Mechanics and Materials 174-177 (May 2012): 2395–98. http://dx.doi.org/10.4028/www.scientific.net/amm.174-177.2395.
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By the context of the tightening energy supply, growing environmental crisis and urban traffic congestion in current China, non-motorized traffic system provides new solutions. This paper learns from the ideas of planning and design of non-motorized traffic system in the other cities and explores the planning of Hangzhou non-motorized traffic system by the key control approach of zoning and classification. The studies show that the non-motorized traffic system planning in Hangzhou mainly proceeds from the pedestrian traffic system and non-motorized transportation system guides the traveling public with a concept of green travel. And it will contribute to achieving cities’ sustainable development by planning an efficient non-motorized traffic system.
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Ratcliffe, B. G., and R. Y. S. Li. "Urban traffic control strategy effects on vehicle fuel consumption." Transportation Planning and Technology 14, no. 1 (June 1989): 53–61. http://dx.doi.org/10.1080/03081068908717413.
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Lou, Xiangqiang, and Quanhua Hou. "The Research on Aggregate Analysis of the Regulatory Detailed Planning by considering the Traffic Capacity." International Journal of Cognitive Informatics and Natural Intelligence 9, no. 1 (January 2015): 1–15. http://dx.doi.org/10.4018/ijcini.2015010101.
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The regulatory detailed planning is substantive legal planning stage of urban planning in China. The first problem is the need to check and inheritance the indicators of total planning land about construction in the process of compiling. According to city zoning rules establishment work reality, the basic thought of the system analysis, the traffic engineering and urban planning in the related theory and method on the basis of macroscopic traffic flow classification, using the road network capacity calculation method and traffic distribution forecasting method proposed with interregional channel planning level of service and the internal road network planning level of service as the control target, proposes the method by using the master planning road network control to inversely calculate the total amount for the construction of district land use. The calculation example is also given. Studies show that the presented control rules compiled for checking algorithm can play check function about the amount of land used for construction master planning achieve under the premise of the control overall situation trunk road network level of service, to avoid the amount of unnecessary in the subsequent units, neighbourhood planning adjustments.
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Gupta, Rajeev. "Development of a Smart Traffic Light Control System Using IoT Technology." Mathematical Statistician and Engineering Applications 70, no. 2 (February 26, 2021): 1112–20. http://dx.doi.org/10.17762/msea.v70i2.2181.
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The development of a smart traffic light control system using IoT technology has become an essential topic in urban traffic management. This research paper focuses on the development of an IoT-based real-time traffic monitoring system for city governance. The system integrates traffic data from various sources, including cameras, sensors, and other data sources, to provide real-time traffic updates to city officials and drivers. The proposed system utilizes IoT technology to collect data from various traffic sources and processes it to determine the optimal time for traffic lights to switch between green, yellow, and red. The system uses a combination of machine learning algorithms and traffic models to predict traffic flow patterns and optimize traffic light timings. Additionally, the system can identify potential traffic accidents and send alerts to nearby emergency services. The proposed system is evaluated using simulation techniques and has shown a significant improvement in reducing traffic congestion and improving traffic flow in a simulated urban environment. Furthermore, the system provides real-time data analytics to city officials, allowing them to make informed decisions on traffic management and city planning. Overall, the development of a smart traffic light control system using IoT technology has significant potential in improving traffic management in urban areas. The proposed system can reduce traffic congestion, improve traffic flow, and enhance overall traffic safety. Therefore, it is essential to continue research and development in this area to implement the proposed system on a larger scale.
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Oskarbski, Jacek, Krystian Birr, and Karol Żarski. "Bicycle Traffic Model for Sustainable Urban Mobility Planning." Energies 14, no. 18 (September 20, 2021): 5970. http://dx.doi.org/10.3390/en14185970.
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Modelling tools and transport models are required to assess the impact of measures for the effective planning of cycling routes in cities. This paper presents the methodology for developing a four-stage macroscopic model of bicycle traffic for the city of Gdynia, and its use in planning new bicycle routes, considering a modal shift. The model presented in this paper allows for the evaluation of the influence of the characteristics of the cycling infrastructure, along with the development of the cycling network based on the choice of cycling as an alternative to other modes of transport, by taking into account the modal shift. The model takes into account the influence of the longitudinal gradient, link, and surface type of cycling routes on the distribution and demand for bicycle traffic. The results of our research allow us to assess the impact of planned cycling routes on the reduction in the volume of car traffic, which is crucial for reducing energy consumption and negative environmental impacts. Experiences from the application of the model in Gdynia suggest that the model provides a strong basis to support mobility planning and monitoring processes in cities worldwide. Cities should take into account the methods proposed in this paper when planning the development of their transport systems.
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Wang, Shaodong, Yanbin Liu, Wei Zhi, Xihua Wen, and Weihua Zhou. "Discovering Urban Functional Polycentricity: A Traffic Flow-Embedded and Topic Modeling-Based Methodology Framework." Sustainability 12, no. 5 (March 2, 2020): 1897. http://dx.doi.org/10.3390/su12051897.
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With the rapid development of communication and transportation technologies, the urban area is increasingly becoming an ever more dynamic, comprehensive, and complex system. Meanwhile, functional polycentricity as a distinctive feature has been characterizing urban areas around the world. However, the spatial structure of the urban area has yet to be fully comprehended from a dynamic perspective, and understanding the spatial organization of polycentric urban regions (PUR) is crucial for issues related to urban planning, traffic control, and urban risk management. The analysis of polycentricity strongly depends on the spatial scale. In order to identify functional polycentricity at the intra-unban scale, this paper presents a traffic flow-embedded and topic modeling-based methodology framework. This framework was evaluated on real-world datasets from the Wujiang district, Suzhou, China, which contains 151,419 records of taxi trajectory data and 86,036 records of points of interest (POI) data. This paper provides a novel approach to examining urban functional polycentricity via combining urban function distribution and spatial interactions. This proposed methodology can help urban authorities better understand urban dynamics in terms of function distribution and internal connectedness and facilitate urban development in terms of urban planning and traffic control.
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Smith, Stephen, Gregory Barlow, Xiao-Feng Xie, and Zachary Rubinstein. "Smart Urban Signal Networks: Initial Application of the SURTRAC Adaptive Traffic Signal Control System." Proceedings of the International Conference on Automated Planning and Scheduling 23 (June 2, 2013): 434–42. http://dx.doi.org/10.1609/icaps.v23i1.13594.
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In this paper, we describe a pilot implementation and field test of a recently developed approach to real-time adaptive traffic signal control. The pilot system, called SURTRAC (Scalable Urban Traffic Control), follows the perspective of recent work in multi-agent planning and implements a decentralized, schedule-driven approach to traffic signal control. Under this approach, each intersection independently (and asynchronously) computes a schedule that optimizes the flow of currently approaching traffic through that intersection, and uses this schedule to decide when to switch green phases. The traffic outflows projected by this schedule are then communicated to the intersection's downstream neighbors, to increase visibility of vehicles entering their respective planning horizons. This process is repeated as frequently as once per second in rolling horizon fashion, to provide real-time responsiveness to changing traffic conditions and coordinated signal network behavior. After summarizing this basic approach to adaptive traffic signal control and the domain challenges it is intended to address, we describe the pilot implementation of SURTRAC and its application to a nine-intersection road network in Pittsburgh, Pennsylvania. Both the SURTRAC architecture for interfacing with the detection equipment, hardware controller and communication network at a given intersection and the extensions required to account for unreliable sensor data are discussed. Finally, we present the results of a pilot test of the system, where SURTRAC is seen to achieve major reductions in travel times and vehicle emissions over pre-existing signal timings.
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Adewale, B. A., and Mozimo Stephanie. "Investigation of The Impact of Noise Control Strategies in Sustainable Building Design." IOP Conference Series: Earth and Environmental Science 1054, no. 1 (September 1, 2022): 012033. http://dx.doi.org/10.1088/1755-1315/1054/1/012033.
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Abstract The design of each city inextricably influences the pattern of noise pollution across the globe. Many aspects of urban planning can significantly affect vehicular distribution, traffic conditions, and the volume of traffic. Lagos State, in particular, is afflicted by some of these factors. Numerous studies have established the significance of noise control strategies in this context. This paper focused on precautionary noise control strategies incorporated at the design stage, which are an integral part of a sustainable urban planning approach. Data were collected via a structured questionnaire from a sample consisting of 96 designers and 67 users of mixed-use buildings in Lagos state; as these building types promote sustainability in building design. This research utilized the Statistical Package for the Social Sciences (SPSS) to analyze data. The results reveal which noise control strategies have been adopted and implemented in sustainable building designs and as a result, its users are not affected by external noise sources. The study’s findings had a positive impact on the implementation of sustainable urban planning strategies that incorporate precautionary noise control strategies.
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Huang, Chenn-Jung, Kai-Wen Hu, Hsing-Yi Ho, and Hung-Wen Chuang. "Congestion-Preventing Routing and Charging Scheduling Mechanism for Electric Vehicles in Dense Urban Areas." Information Technology and Control 50, no. 2 (June 17, 2021): 284–307. http://dx.doi.org/10.5755/j01.itc.50.2.27780.
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Traffic congestion in metropolitan areas all over the world has become a critical issue that governments mustdeal with effectively. Traffic congestion during rush hours causes vehicle drivers to arrive late at their destinations,resulting in significant economic losses. Although researchers have proposed solutions to the traffic congestionproblem, little research work has presented a joint route and charging planning strategy for electric vehicles(EVs) that alleviates traffic congestion problems simultaneously. Accordingly, a congestion-preventing route and charging planning mechanism for EVs is proposed in this work to tackle the complicated route and charging optimizationproblems of EVs. The route and charging planning proposed in this work analyzes the information providedby EVs, the charging points, and road traffic information simultaneously, and mediates the traffic jammingby means of a route and charging reservation mechanism. Possible occurrence of traffic congestion is detectedin advance and traffic regulation is carried out by allocating an elastic range to the traveling period for late-bookingEVs, to avoid moving during rush hours. EV owners are also encouraged to provide rideshare services forlate-booking EV users during rush hours. The simulation results reveal that the proposed work can satisfy thepreferred route and charging demands of EV users and alleviate traffic congestion effectively.
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Germanova, Tatiana, and Anna Kernozhitskaya. "TO A QUESTION OF ECOLOGICAL ASSESSMENT OF A CONDITION OF INHABITED TERRITOÉRIES NEAR TRAFFIC FLOWS." Akustika 32 (March 1, 2019): 312–15. http://dx.doi.org/10.36336/akustika201932312.
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Planning to transport can be hi-tech process which often leans on computer models and other difficult tools for modeling. In this article describes the transportation planning process and the legal/regulatory foundation in Russia for much of what occurs in transportation planning today. Local governments can influence transportation plannings through their control of local street systems as well as their legal responsibilities for land-use zoning. Also describes those factors that influence land use and urban form. This article references Russia environmental laws regulations to illustrate general principles and provide a framework for discussion.
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Yan, Longhao, Ping Wang, Jingwen Yang, Yu Hu, Yu Han, and Junfeng Yao. "Refined Path Planning for Emergency Rescue Vehicles on Congested Urban Arterial Roads via Reinforcement Learning Approach." Journal of Advanced Transportation 2021 (August 31, 2021): 1–12. http://dx.doi.org/10.1155/2021/8772688.
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Fast road emergency response can minimize the losses caused by traffic accidents. However, emergency rescue on urban arterial roads is faced with the high probability of congestion caused by accidents, which makes the planning of rescue path complicated. This paper proposes a refined path planning method for emergency rescue vehicles on congested urban arterial roads during traffic accidents. Firstly, a rescue path planning environment for emergency vehicles on congested urban arterial roads based on the Markov decision process is established, which focuses on the architecture of arterial roads, taking the traffic efficiency and vehicle queue length into consideration of path planning; then, the prioritized experience replay deep Q-network (PERDQN) reinforcement learning algorithm is used for path planning under different traffic control schemes. The proposed method is tested on the section of East Youyi Road in Xi’an, Shaanxi Province, China. The results show that compared with the traditional shortest path method, the rescue route planned by PERDQN reduces the arrival time to the accident site by 67.1%, and the queue length at upstream of the accident point is shortened by 16.3%, which shows that the proposed method is capable to plan the rescue path for emergency vehicles in urban arterial roads with congestion, shorten the arrival time, and reduce the vehicle queue length caused by accidents.
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Zhao, Xueting, Liwei Hu, Xingzhong Wang, and Jiabao Wu. "Study on Identification and Prevention of Traffic Congestion Zones Considering Resilience-Vulnerability of Urban Transportation Systems." Sustainability 14, no. 24 (December 16, 2022): 16907. http://dx.doi.org/10.3390/su142416907.
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In order to solve the problem of urban short-term traffic congestion and temporal and spatial heterogeneity, it is important to scientifically delineate urban traffic congestion response areas to alleviate regional traffic congestion and improve road network efficiency. Previous urban traffic congestion zoning is mostly divided by urban administrative divisions, which is difficult to reflect the difference of congestion degree within administrative divisions or traffic congestion zoning. In this paper, we introduce the Self-Organizing Feature Mapping (SOFM) model, construct the urban traffic congestion zoning index system based on the resilience and vulnerability of urban traffic systems, and establish the urban traffic congestion zoning model, which is divided into four, five, six, and seven according to the different structures of competition layer topology. The four vulnerability damage capacity indicators of traffic volume, severe congestion mileage, delay time and average operating speed, and two resilience supply capacity indicators of traffic systems, namely, road condition and number of lanes, are used as model input vectors; the data of Guiyang city from January to June 2021 are used as data sets to input four SOFM models for training and testing and the best SOFM model with six competitive topologies is constructed. Finally, the Support Vector Machine (SVM) is used to identify the optimal partition boundary line for traffic congestion. The results show that the four models predict the urban traffic congestion zoning level correctly over 95% on the test set, each traffic congestion zoning evaluation index in the urban area shows different obvious spatial clustering characteristics, the urban traffic congestion area is divided into six categories, and the city is divided into 16 zoning areas considering the urban traffic congestion control types (prevention zone, control zone, closure control zone). The spatial boundary is clear and credible, which helps to improve the spatial accuracy when predicting urban traffic congestion zoning and provides a new methodological approach for urban traffic congestion zoning and zoning boundary delineation.
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Esser, J., and M. Schreckenberg. "Microscopic Simulation of Urban Traffic Based on Cellular Automata." International Journal of Modern Physics C 08, no. 05 (October 1997): 1025–36. http://dx.doi.org/10.1142/s0129183197000904.
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Saturated capacities in traffic systems evoke increasing interest in simulations of complex networks serving as laboratory environment for developing management strategies. Especially for urban areas questions concerning overall traffic control have to be considered with regard to their impacts on the whole network. Modeling traffic flow dynamics using cellular automata allows us to run large network traffic simulations with only comparatively low computational efforts. We present a traffic simulation tool for urban road networks which is based on the Nagel–Schreckenberg Model. Arbitrary kinds of roads and crossings are modeled as combinations of only a few basic elements. Furthermore parking capacities are considered as well as circulations of public transports. The vehicles are driven corresponding to route plans or at random depending on the available data. The application of this network simulation covers investigations on the field of traffic planning as well as online simulations based on real-time traffic data as basis for dynamic traffic management systems.
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Maadi, Saeed, Sebastian Stein, Jinhyun Hong, and Roderick Murray-Smith. "Real-Time Adaptive Traffic Signal Control in a Connected and Automated Vehicle Environment: Optimisation of Signal Planning with Reinforcement Learning under Vehicle Speed Guidance." Sensors 22, no. 19 (October 3, 2022): 7501. http://dx.doi.org/10.3390/s22197501.
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Adaptive traffic signal control (ATSC) is an effective method to reduce traffic congestion in modern urban areas. Many studies adopted various approaches to adjust traffic signal plans according to real-time traffic in response to demand fluctuations to improve urban network performance (e.g., minimise delay). Recently, learning-based methods such as reinforcement learning (RL) have achieved promising results in signal plan optimisation. However, adopting these self-learning techniques in future traffic environments in the presence of connected and automated vehicles (CAVs) remains largely an open challenge. This study develops a real-time RL-based adaptive traffic signal control that optimises a signal plan to minimise the total queue length while allowing the CAVs to adjust their speed based on a fixed timing strategy to decrease total stop delays. The highlight of this work is combining a speed guidance system with a reinforcement learning-based traffic signal control. Two different performance measures are implemented to minimise total queue length and total stop delays. Results indicate that the proposed method outperforms a fixed timing plan (with optimal speed advisory in a CAV environment) and traditional actuated control, in terms of average stop delay of vehicle and queue length, particularly under saturated and oversaturated conditions.
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Gorbachev, A. M. "Mathematical model of aperiodic timetables of urban electric transport." Automation on Transport 6, no. 4 (December 2020): 499–517. http://dx.doi.org/10.20295/2412-9186-2020-6-4-499-517.
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The analysis of scientifi c publications and timetable models is given. Existing works have been used as a basis of a classification of timetables by the frequency of time values. The urban transport network is presented in the form of a multigraph. The transition from a multigraph of the urban transport network to a network of events characterizing the traffi c process is considered. Constraints on time values have been formalized to solve the main problem of the scheduling theory. The proposed formalization factors in the specifi cs of traffic management planning in Russia and other post-Soviet countries. A mathematical model of aperiodic timetables for the ground urban electric transport traffic based on the theory of linear programming is presented. The optimization criterion for solving the main problem of the scheduling theory has been substantiated. The uniformity of traffi c intervals is used as an optimization criterion for solving the main problem of the scheduling theory. The article provides tabular timetables used in urban transport to describe the traffi c process in the absence of significant events on the line. The implementation of the model presented in this article is exemplified by the automated tram and trolleybus timetable design software being part of the automated urban electric transport control system currently used in Saint Petersburg to form tram and trolleybus timetables. The examples of calculating the vehicle departure interval diagrams have been used to demonstrate the function of aligning the traffi c intervals. In conclusion, the advantages and development paths of the proposed model of aperiodic timetables for the ground urban electric transport traffic are listed
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Dzoljic, Jovana, Vladimir Popovic, Srdjan Jovkovic, and Jovan Misic. "Urban traffic air pollution - case study City of Vranje, Serbia." IOP Conference Series: Earth and Environmental Science 1123, no. 1 (December 1, 2022): 012084. http://dx.doi.org/10.1088/1755-1315/1123/1/012084.
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Abstract The expansion of urban areas with unequal, rapidly growing population results in higher vehicle numbers in the cities. Traffic in the urban environment is one of the main concerns, since it is one of the most prominent sources of air pollution, connected to the mortality rate. Regarding the Sustainable Development Goals (SDG) and SDG 11, urban areas should meet environmental needs following the process of environmental transition. The Vranje city, Serbia follows the global trend of vehicle number increment. Regarding the specific geomorphological and climate conditions, it is of importance to emphasize the traffic air pollution control in the urban environment. Numerous studies found that vehicular exhaust emissions near traffic intersections are largely dependent on fleet speed, queuing time in idle mode with a red signal time, traffic-flow rate, ambient conditions, etc. Traffic management has the key role, especially regarding the intersection of traffic flows, since there are time losses on the intersections’ driveways that increase the energy consumption to overcome certain conflict flows. The scope of this study should point out the importance of traffic planning and management, especially at the traffic flows for reducing air pollution in the urban environment.
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Liu, Meiqi, Meng Wang, and Serge Hoogendoorn. "Optimal Platoon Trajectory Planning Approach at Arterials." Transportation Research Record: Journal of the Transportation Research Board 2673, no. 9 (May 5, 2019): 214–26. http://dx.doi.org/10.1177/0361198119847474.
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Cooperative (automated) vehicles have the potential to enhance traffic efficiency and fuel economy on urban roads, especially at signalized intersections. An optimal control approach to optimize the trajectories of cooperative vehicles at fixed-timing signalized intersections along an arterial is presented. The proposed approach aims to optimize throughput first, and then to maximize comfort while minimizing travel delay and fuel consumption. The proposed approach is flexible in dealing with both quadratic and more complex cost functions. Assuming fixed timing signal control in a cycle and vehicle-to-infrastructure communication, the red phase is taken into account in position constraints for vehicles that cannot pass the intersection in the green phase. Safety is guaranteed by constraining the inter-vehicle distance larger than some desired value. The approach is scalable and can be used for joint trajectory planning of one platoon approaching another stationary platoon. It can also be extended to multiple intersections with fixed signal plans. To verify the performances of the controlled platoon, simulation under three different traffic scenarios is conducted, namely: an isolated intersection with/without downstream vehicle queues, and platoon control at multiple intersections. Three baseline scenarios without control are also designed to compare performances in relation to both mobility and fuel consumption in each controlled scenario. The results demonstrate that the controlled vehicles generate plausible behavior under control objectives and constraints. Moreover, the consideration of downstream vehicle queues and the application at both an isolated signalized intersection and arterial corridors on urban roads verify the flexible characteristics of the control framework.
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Gong, Guimin, Wenhong Lv, and Qi Wang. "Research on Urban Road Traffic Network Pinning Control Based on Feedback Control." Sustainability 15, no. 12 (June 15, 2023): 9631. http://dx.doi.org/10.3390/su15129631.
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The development and application of pinning control methods create conditions for traffic area control, and the objective of possessing global control of the road network is achieved by controlling a small number of intersections in the road network. Based on this, an urban road network pinning control strategy is designed in this paper. Firstly, this paper establishes the state equation of the urban road traffic network according to the characteristics of traffic flow, and proposes an associated state equation for road sections and key intersections. Secondly, by adjusting the signal timing scheme of key intersections as the target of pinning control, it can restrain the road network to achieve the state with the minimum difference between the actual flow and the desired flow on each road section. At the same time, considering the dynamic nature of traffic flow and the fact that the flow rate on the road section changes continuously, a feedback control mechanism is established in order to determine the threshold value at which each road section enters the congestion state. In addition, when the flow rate of a road section exceeds its threshold value to reach the congestion state, the signal timing scheme of the key intersection needs to be adjusted again to ensure that the flow rate on the road section is always lower than the threshold value at which it enters the congestion state. The results show that the average delay time and average stopping time of the road network are reduced by 35.03s and 18.37s, respectively, compared with the original control scheme, proving that the control strategy can effectively reduce congestion and improve the operational efficiency of the road network.
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Chrpa, Lukáš, Daniele Magazzeni, Keith McCabe, Thomas L. McCluskey, and Mauro Vallati. "Automated planning for Urban traffic control: Strategic vehicle routing to respect air quality limitations." Intelligenza Artificiale 10, no. 2 (December 12, 2016): 113–28. http://dx.doi.org/10.3233/ia-160099.
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Vrbanić, Filip, Mladen Miletić, Leo Tišljarić, and Edouard Ivanjko. "Influence of Variable Speed Limit Control on Fuel and Electric Energy Consumption, and Exhaust Gas Emissions in Mixed Traffic Flows." Sustainability 14, no. 2 (January 14, 2022): 932. http://dx.doi.org/10.3390/su14020932.
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Modern urban mobility needs new solutions to resolve high-complexity demands on urban traffic-control systems, including reducing congestion, fuel and energy consumption, and exhaust gas emissions. One example is urban motorways as key segments of the urban traffic network that do not achieve a satisfactory level of service to serve the increasing traffic demand. Another complex need arises by introducing the connected and autonomous vehicles (CAVs) and accompanying additional challenges that modern control systems must cope with. This study addresses the problem of decreasing the negative environmental aspects of traffic, which includes reducing congestion, fuel and energy consumption, and exhaust gas emissions. We applied a variable speed limit (VSL) based on Q-Learning that utilizes electric CAVs as speed-limit actuators in the control loop. The Q-Learning algorithm was combined with the two-step temporal difference target to increase the algorithm’s effectiveness for learning the VSL control policy for mixed traffic flows. We analyzed two different optimization criteria: total time spent on all vehicles in the traffic network and total energy consumption. Various mixed traffic flow scenarios were addressed with varying CAV penetration rates, and the obtained results were compared with a baseline no-control scenario and a rule-based VSL. The data about vehicle-emission class and the share of gasoline and diesel human-driven vehicles were taken from the actual data from the Croatian Bureau of Statistics. The obtained results show that Q-Learning-based VSL can learn the control policy and improve the macroscopic traffic parameters and total energy consumption and can reduce exhaust gas emissions for different electric CAV penetration rates. The results are most apparent in cases with low CAV penetration rates. Additionally, the results indicate that for the analyzed traffic demand, the increase in the CAV penetration rate alleviates the need to impose VSL control on an urban motorway.
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Maffei, Luigi, and Massimiliano Masullo. "Electric Vehicles and Urban Noise Control Policies." Archives of Acoustics 39, no. 3 (March 1, 2015): 333–41. http://dx.doi.org/10.2478/aoa-2014-0038.
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Abstract Limited Traffic Zone (LTZ) is a planning strategy that is more and more adopted by municipalities in Europe to improve their environmental conditions. It consists in the prohibition for traditional vehicles to circulate in specific areas. Although the main aim is to tackle air pollution problems, positive effects are registered in terms of reduction of noise annoyance and in terms of improved “quality of life” if specific conditions are respected. On the other side under the drive of the global market, the number of circulating electric vehicles in urban sites is also increasing. In the next years we expect to experience a new and not well-known urban soundscape. In this paper is presented an overview of recent urban projects and policies that deal with noise control and how these experiences will match into the next years with the sound characteristics of new electric vehicles for private and public transportation.
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Li, Bo, Yue Wang, Tong Wang, Xiaoman He, and Jan K. Kazak. "Scenario Analysis for Resilient Urban Green Infrastructure." Land 11, no. 9 (September 4, 2022): 1481. http://dx.doi.org/10.3390/land11091481.
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With the advancement of urbanization, the stress on the green infrastructure around the urban agglomeration has intensified, which causes severe ecological problems. The uncertainty of urban growth makes it difficult to achieve effective protection only by setting protection red lines and other rigid measures. It is of practical significance to optimize the resilience of the stressed green infrastructure. To this end, we explore a scenario simulation analysis method for the resilience management of green infrastructure under stress. This research applies artificial neural network cellular automata to simulate the impacts of the Chang-Zhu-Tan urban agglomeration expansion on the green infrastructure in 2030 in three scenarios: no planning control, urban planning control, and ecological protection planning control. Based on the analysis, we identify four green infrastructure areas under stress and formulate resilience management measures, respectively. The results show that: (1) The distribution pattern of green infrastructure under stress is different in three scenarios. Even in the scenario of ecological protection planning and control, urban growth can easily break through the ecological protection boundary; (2) Residential, industrial, and traffic facility land are the main types of urban land causing green infrastructure stress, while forest, shrub, and wetland are the main types of the stressed green infrastructure; (3) Efficient protection of green infrastructure and the management of the urban growth boundary should be promoted by resilient management measures such as urban planning adjustment, regulatory detailed planning, development strength control and setting up the ecological protection facilities for the stressed green infrastructure areas of the planning scenarios and the no-planning control scenarios, for the areas to be occupied by urban land, and for the important ecological corridors. The results of this study provide an empirical foundation for formulating policies and the methods of this study can be applied to urban ecological planning and green infrastructure management practice in other areas as well.
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Katerinin, K. V., B. Kh Sanzhapov, B. A. Bondarev, and M. N. Dyatlov. "APPLICATION OF THE GRAPH-ANALYTIC APPROACH IN THE DESIGN OF TRAFFIC LIGHT CONTROL SCHEMES ON URBAN ROAD SECTIONS." Russian Journal of Building Construction and Architecture, no. 4(56) (November 16, 2022): 74–83. http://dx.doi.org/10.36622/vstu.2022.56.4.007.
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Statement of the problem. The applied scheme of the organization of traffic light regulation of urban traffic is one of the key factors determining the convenience and environmental friendliness of the functioning of the entire transport infrastructure of the city. Optimization of its parameters is the simplest and most cost-effective way to increase the comfort of moving along urban highways and improve the overall environmental situation. Results. The use of a graphical large-scale traffic flow diagram as a simple and convenient tool for analyzing and optimizing the traffic light regulation scheme on the section of the dominant highway of the road network is considered. As an example, an optimized version of the traffic light regulation scheme on Raboche-Krestyanskaya Street in the city of Volgograd is shown. Conclusions. The proposed graph-analytic approach allows one to quickly and visually develop, analyze, and, if necessary, optimize the parameters of the traffic light control scheme on problematic sections of urban highways.
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Zhang, Linan, Yizhe Wang, and Huaizhong Zhu. "Theory and Experiment of Cooperative Control at Multi-Intersections in Intelligent Connected Vehicle Environment: Review and Perspectives." Sustainability 14, no. 3 (January 28, 2022): 1542. http://dx.doi.org/10.3390/su14031542.
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A heterogeneous traffic flow consists of regular vehicles, and intelligent connected vehicles having interactive functions is updating the composition of the current urban-road network traffic flow. It has been a growing trend and will continue to be so. Because of the urgent demand, the research focused on three main parts of cooperative control methods under intelligent connected vehicles environment, typical traffic control application scenarios and experimental validation in intelligent connected vehicles conditions, and intersection-oriented hybrid traffic control mechanism for urban road. For heterogeneous interrupted traffic flow of intelligent connected vehicles, to analyze the characteristics and information extraction method of heterogeneous traffic flow of intelligent connected vehicles under different conditions, the research examined driving modes of regular vehicles and intelligent connected vehicles, including car following and lane changing. This study summarized control modes of traffic-signal control, active control of intelligent connected vehicles, and indirect control of regular vehicles through intelligent vehicles to study the active control mechanism and multi-intersection coordinated control strategy for intelligent connected vehicle heterogeneous traffic flow. With the combination of coordinated control theory, this work overviewed integrated experiment of information interaction and coordinated control under intelligent-connected-vehicle heterogeneous traffic-flow environments.
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Liu, Li Rong, Yong Liu, Xin Yuan Li, and Xin Li. "Low Carbon Industrial Park Green Infrastructure Planning Control Strategies Discussed." Advanced Materials Research 962-965 (June 2014): 1664–69. http://dx.doi.org/10.4028/www.scientific.net/amr.962-965.1664.
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The main purpose of this paper is to optimize the developing pattern of the industrial park, make it fully work for the social environment and economic benefit. Based on green infrastructure and function analysis, this paper discusses about the planning control paths of building the elastic ecological pattern, water recycle, clean energy, green traffic and planning control system by putting the concept of green infrastructure into the linkage of the industrial park and urban construction process. It also proposed the control strategy, which combined low-carbon development of industrial park with green infrastructure, to boost a sustainable development of low-carbon green industrial park.
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Ranpise, Ramesh B., and Bhaven N. Tandel. "Urban road traffic noise monitoring, mapping, modelling, and mitigation: A thematic review." Noise Mapping 9, no. 1 (January 1, 2022): 48–66. http://dx.doi.org/10.1515/noise-2022-0004.
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Abstract This article analyses the most recent studies on urban traffic noise. About 67 relevant articles on urban road traffic noise and its mitigation strategies were preferred for a critical review. Only 5.97% of items describe how to monitor and record the noise measurement for urban roads, while 7.46% of articles enumerated urban traffic noise pollution exposure. 29.85% of articles proposed a model to evaluate noise reduction effects and predict the noise level. Also, many articles reported noise map generation and its analysis. 56.71% of articles described the noise mitigation strategies in detail, concerning noise control by green vegetation, land use planning, low noise tire and pavement material, noise reduction through façade shielding. Noise pollution standards are being breached in all areas. There is a need for the proper implementation of rules and regulations. Therefore, noise mitigation strategies such as designing noise barriers and other noise control materials are needed. Finally, it is summarized that economic and low-cost optimized noise pollution mitigation strategies like ingeniously made noise barriers, vegetation and landscaping are need of the hour for urban areas of developing countries.
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Ji, Ke, Jinjun Tang, Min Li, and Cheng Hu. "Distributed Traffic Control Based on Road Network Partitioning Using Normalization Algorithm." Sustainability 15, no. 14 (July 21, 2023): 11378. http://dx.doi.org/10.3390/su151411378.
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With continuous economic development, most urban road networks are facing unprecedented traffic congestion. Centralized traffic control is difficult to achieve, and distributed traffic control based on partitioning a road network into subnetworks is a promising way to alleviate traffic pressure on urban roads. In order to study the differences between different partitioning methods chosen for distributed traffic control, we used the normalization algorithm to partition a part of the road network in Changsha City, and we used the results of the Girvan–Newman algorithm and the manual empirical partitioning method as a control group. Meanwhile, an abstract road network was constructed using VISSIM simulation software based on realistic road network parameters. And then, the different partitioning results were applied to the simulated road network to analyze the control effect. The results of the simulation software show that different partitioning methods have different effects on traffic control at subnetwork boundaries and improve traffic pressure to different degrees. Partitioning the road network into four subnetworks provided the greatest degree of traffic improvement. Overall, the proposed distributed traffic control method effectively improved operational efficiency and alleviated the traffic pressure of the road network.
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Hu, Hsu-Chieh, and Stephen F. Smith. "Learning Model Parameters for Decentralized Schedule-Driven Traffic Control." Proceedings of the International Conference on Automated Planning and Scheduling 30 (June 1, 2020): 531–39. http://dx.doi.org/10.1609/icaps.v30i1.6749.
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Model-based intersection optimization strategies that produce signal timings over a specified optimization horizon have been widely investigated for urban traffic signal control, and recent work in this area produced a scalable approach to real-time traffic control based on a decentralized schedule-driven optimization model. In this approach, a scheduling agent is associated with each intersection. Each agent senses the traffic approaching its intersection through local sensors and in real-time constructs a schedule that minimizes the cumulative wait time of vehicles approaching the intersection over the current look-ahead horizon. Intersections then exchange schedule information with their neighbors to achieve network level coordination. Although the approach is general and has demonstrated substantial success, its effectiveness in a given road network depends on the extent to which various parameters of the model, e.g, maximum green time, are adjusted to match that network's actual flow conditions over time. To address this problem, we propose a two-stage hierarchical structure that combines online planning and reinforcement learning. Reinforcement learning is applied to adjust the parameters of the model over a longer time-scale. On the other hand, online planning is used to compute the schedule for managing the traffic signals in the shorter term. We demonstrate how this hybrid approach outperforms the original approach in real-time traffic signal control problems.
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Jafari, Sadiqa, Zeinab Shahbazi, and Yung-Cheol Byun. "Improving the Performance of Single-Intersection Urban Traffic Networks Based on a Model Predictive Controller." Sustainability 13, no. 10 (May 18, 2021): 5630. http://dx.doi.org/10.3390/su13105630.
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The use of a Model Predictive Controller (MPC) in an urban traffic network allows for controlling the infrastructure of a traffic network and errors in its operations. In this research, a novel, stable predictive controller for urban traffic is proposed and state-space dynamics are used to estimate the number of vehicles at an isolated intersection and the length of its queue. This is a novel control strategy based on the type of traffic light and on the duration of the green-light phase and aims to achieve an optimal balance at intersections. This balance should be adaptable to the unchanging behavior of time and to the randomness of traffic situations. The proposed method reduces traffic volumes and the number of crashes involving cars by controlling traffic on an urban road using model predictive control. A single intersection in Tehran, the capital city of Iran, was considered in our study to control traffic signal timing, and model predictive control was used to reduce traffic. A model of traffic systems was extracted at the intersection, and the state-space parameters of the intersection were designed using the model predictive controller to control traffic signals based on the length of the vehicle queue and on the number of inbound and outbound vehicles, which were used as inputs. This process demonstrates that this method is able to reduce traffic volumes at each leg of an intersection and to optimize flow in a road network compared to the fixed-time method.
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Wu, Qiong, Xiaofeng Zhang, and Guanghua Cao. "Study on the prevention and control measures of China’s urban road traffic noise pollution." E3S Web of Conferences 96 (2019): 03003. http://dx.doi.org/10.1051/e3sconf/20199603003.
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Just like the other countries in the world, urban road traffic noise pollution is widespread in China, and with the acceleration of its urbanization process, noise pollution continuously arises. However, China’s legislation and governance measures on noise pollution control began in 1989, which is relatively late. Based on the urban road traffic noise pollution status and typical cities’ measures in China, and combined with the successful experiences of developed countries, this paper analyzes the causes and puts forward corresponding prevention and control measures from five aspects, such as improving the laws and regulations, focusing on planning and design, thinking highly of Noise Mapping, carrying out special noise reduction projects and strengthening management measures, as a reference for the relevant jurisdictions and scientific researchers.
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Keler, Andreas, Patrick Malcolm, Georgios Grigoropoulos, and Klaus Bogenberger. "Designing Maps for Bicycling Simulator Studies – three practical Approaches." Proceedings of the ICA 4 (December 3, 2021): 1–4. http://dx.doi.org/10.5194/ica-proc-4-59-2021.
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Abstract. Bicycle simulator studies result from attempts of solving various novel problem statements of modern transportation-related research questions. Examples imply the evaluation of novel traffic control strategies for prioritizing urban bicycle traffic, novel bicycle infrastructure (such as bicycle highways) and the interaction and communication of vulnerable road users with automated or autonomous vehicles. As one of classical disciplines of transportation research, namely traffic engineering, and less related to human factors research, automotive research, geography, urban planning or citizen science, we want to point out those bicycle simulator studies design approaches, which are more related to testing novel traffic control strategies for cyclists, experiencing changing traffic-efficiency and –safety-related parameters in ongoing interfaced microscopic traffic flow simulations. We believe that this is a key factor in experiencing various traffic situations and the evaluation of thereof. In this research, we introduce three practical approaches of how to design maps for bicycling simulator studies. This is mainly resulting from manifold practical experiences from already conducted simulator studies beginning from the year 2018.
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Zeng, Jun-Wei, Yong-Sheng Qian, Hui Wang, and Xu-Ting Wei. "Modeling and simulation of traffic flow under different combination setting of taxi stop and bus stop." Modern Physics Letters B 32, no. 25 (September 5, 2018): 1850301. http://dx.doi.org/10.1142/s0217984918503013.
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Taxis and buses have significant influence on traffic flow due to their special moving and stopping behavior. Based on the analysis of their operation and stopping characteristics, a two-lane cellular automaton model for urban roads considering the influence of stopping behavior is established, the vehicle type, cell length and moving speed are re-described. Considering the linear taxi stop and the linear bus stop, the characteristics of traffic flow under two different combination settings are studied. The numerical simulation results show that the combined bottleneck effect has little impact on flow rate and average speed when the bus stop is set on the upstream of the taxi stop, and the distance between stops should be 50 m. These findings lay a solid foundation for better description of urban traffic flow and enable better scientific planning and control of urban traffic.
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Amaral, Rodrigo Rezende, Ivana Semanjski, Sidharta Gautama, and El-Houssaine Aghezzaf. "Exploring the issue of integrating logistics and traffic control in urban areas." Transportation Planning and Technology 42, no. 6 (June 3, 2019): 606–24. http://dx.doi.org/10.1080/03081060.2019.1622253.
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Fang, Xuan, Tamás Péter, and Tamás Tettamanti. "Variable Speed Limit Control for the Motorway–Urban Merging Bottlenecks Using Multi-Agent Reinforcement Learning." Sustainability 15, no. 14 (July 24, 2023): 11464. http://dx.doi.org/10.3390/su151411464.
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Traffic congestion is a typical phenomenon when motorways meet urban road networks. At this special location, the weaving area is a recurrent traffic bottleneck. Numerous research activities have been conducted to improve traffic efficiency and sustainability at bottleneck areas. Variable speed limit control (VSL) is one of the effective control strategies. The primary objective of this paper is twofold. On the one hand, turbulent traffic flow is to be smoothed on the special weaving area of motorways and urban roads using VSL control. On the other hand, another control method is provided to tackle the carbon dioxide emission problem over the network. For both control methods, a multi-agent reinforcement learning algorithm is used (MAPPO: multi-agent proximal policy optimization). The VSL control framework utilizes the real-time traffic state and the speed limit value in the last control step as the input of the optimization algorithm. Two reward functions are constructed to guide the algorithm to output the value of the dynamic speed limit enforced within the VSL control area. The effectiveness of the proposed control framework is verified via microscopic traffic simulation using simulation of urban mobility (SUMO). The results show that the proposed control method could shape a more homogeneous traffic flow, and reduces the total waiting time over the network by 15.8%. In the case of the carbon dioxide minimization strategy, the carbon dioxide emission can be reduced by 10.79% in the recurrent bottleneck area caused by the transition from motorways to urban roads.
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Raub, Richard A., and Joseph L. Schofer. "Managing Incidents on Urban Arterial Roadways." Transportation Research Record: Journal of the Transportation Research Board 1603, no. 1 (January 1997): 12–19. http://dx.doi.org/10.3141/1603-02.
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Limiting the impact on traffic of nonrecurring events such as crashes, traffic stops, or disabled vehicles through effective incident management should be one objective for emergency response professionals. Moreover, such management is an integral part of Intelligent Transportation Systems planning. The Arterial Incident Management Study, sponsored by the Illinois Department of Transportation and conducted by Northwestern University, examined the impact and management of arterial street incidents to determine what steps could be taken to improve the handling of such events. Several approaches were used to accomplish this, including (a) analysis of incident data from police and fire agencies, (b) debriefings of responders about specific incidents, (c) observation and videotaping of incidents, and (d) an incident management simulation workshop involving police, fire, emergency medicine, tow operator, public works, insurance, and media professionals who have responsibilities for incident management. A series of incidents were simulated in a workshop and consensus was sought on specific and general management tactics. This paper describes study methods and summarizes the important issues and recommendations to improve incident management. Among the key needs identified are (a) response in a manner and with adequate resources to minimize the time an incident affects a scene, (b) rapid removal of vehicles and debris, (c) effective traffic control at and around the incident, (d) communication with motorists who may be affected by long-duration incidents, and (e) advanced, intra- and interagency planning for incident management. Recommended changes include education of drivers and professionals, legislation, communications, use of new technologies for communications and data collection, and advanced planning and coordination of on-site procedures, responsibilities, and priorities.
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Al-Mousa, Amjed, Belal H. Sababha, Nailah Al-Madi, Amro Barghouthi, and Remah Younisse. "UTSim: A framework and simulator for UAV air traffic integration, control, and communication." International Journal of Advanced Robotic Systems 16, no. 5 (September 1, 2019): 172988141987093. http://dx.doi.org/10.1177/1729881419870937.
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The interest in unmanned systems especially unmanned aerial vehicle is continuously increasing. Unmanned aerial vehicles started to become of great benefit in many different fields. It is anticipated that unmanned aerial vehicles will soon become a main component of the future urban air traffic. The integration of unmanned aerial vehicles within existing air traffic environments has started getting the attention of researchers. Integrating unmanned systems in the real-world urban air traffic requires the development of tools and simulators to enable researchers in their ongoing efforts. In this article, a simulator called UTSim is introduced. The proposed simulator is built using the Unity platform. UTSim is capable of simulating unmanned aerial vehicle physical specification, navigation, control, communication, sensing and avoidance in environments with static and moving objects. The simulator enables studying and exploring several unmanned aerial vehicle air traffic integration issues like sense and avoid, communication protocols, navigation algorithms, and much more. UTSim is designed and developed to be easily used. The user can specify the properties of the environment, the number and types of unmanned aerial vehicles in the environment, and specify the algorithm to be used for path planning and collision avoidance. The simulator outputs a log file with a lot of useful information such as the number of sent and received messages, the number of detected objects and collided unmanned aerial vehicles. Three scenarios have been implemented in this article to present the capabilities of UTSim and to illustrate how it can benefit researchers in the field of integrating unmanned aerial vehicles in urban air traffic.
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Zhang, Rui, Fei Xie, Jianjun Shi, Jing Zhao, Jiquan Yang, and Xu Ling. "Spatial-Temporal Semantic Neural Network for Time Series Forecasting." Journal of Physics: Conference Series 2203, no. 1 (February 1, 2022): 012033. http://dx.doi.org/10.1088/1742-6596/2203/1/012033.
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Abstract Time series forecasting play an important role in many applications, and combining neural networks to forecast time series features can uncover many potential application situations. For example, forecasting traffic flow time series data is important for urban traffic planning and traffic management. Accurate forecasting of traffic flow provides the basis for road traffic control, which in turn improves traffic efficiency and reduces congestion. In this paper, STSeNN is proposed, which combines graph neural network and TCN to dynamically capture the spatial correlation, temporal correlation and semantic correlation of data. Experiments show that the prediction performance of STSeNN on the traffic flow datasets is more accurate compared with existing methods.
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Wu, Yanming, Uta Pottgiesser, Wido Quist, and Qi Zhou. "The Guidance and Control of Urban Planning for Reuse of Industrial Heritage: A Study of Nanjing." Land 11, no. 6 (June 5, 2022): 852. http://dx.doi.org/10.3390/land11060852.
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Industrial heritage is among the products of modern urban development, and the influencing factors of its regeneration and development are often complex. Due to different national conditions, the research progress and approaches in industrial heritage reuse in China are different from other countries. While industrial heritage sites in Europe have become part of urban redevelopment in several regions, China still focuses mostly on single objects, lacking systematic analysis, especially at the urban scale. Regarding the city of Nanjing, an operational approach to complex urban dynamics is proposed based on a simplified analysis of official statistics, maps and GIS technology. The influence mechanisms of Nanjing’s urban planning on industrial heritage regeneration and development after 1990 are analyzed. The results show that urban growth boundaries, traffic accessibility, eco-environmental policies, population distribution, industrial renovation investment and natural resource change all have a significant impact on the abandonment and regeneration of Nanjing industrial heritage. This study expands the research perspective of industrial heritage reuse in China and proposes a clearer systematic planning strategy for the future of industrial heritage in cities.
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Yu, Ning. "Urban Rail Transit Network Planning Based on Particle Swarm Optimization Algorithm." Mathematical Problems in Engineering 2022 (August 21, 2022): 1–9. http://dx.doi.org/10.1155/2022/2401333.
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In order to solve the problem that the urban rail transit network is affected by a large number of signals, resulting in poor control effect, and improve the living comfort of residents near urban rail transit, a study on urban rail transit network planning based on particle swarm optimization algorithm is proposed. The learning factor is dynamically adjusted according to the inertia weight parameters, and the particle swarm optimization parameters are selected in combination with the setting of the maximum velocity parameters. The individual optimal particle is selected by using the dominant relationship between the individual particles, and the optimization of the optimal particle is completed by combining the selection requirements of the global optimal particle. We design the v2x communication implementation scheme, obtain the traffic flow information of urban rail transit, build the signal input and output model based on particle swarm optimization algorithm, obtain the output feedback signal, and determine the planning scale of urban rail transit network, so as to build the urban rail transit network planning model and complete the urban rail transit network planning. The experimental results show that the proposed method can improve the utilization rate of urban rail transit network planning, effectively control the change of network signal amplitude, and reduce the repetition rate of urban rail transit network planning.
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Wei, Xiao Wei. "The Analysis of Traffic Flow Model." Applied Mechanics and Materials 380-384 (August 2013): 237–40. http://dx.doi.org/10.4028/www.scientific.net/amm.380-384.237.
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With worsening traffic condition in large and medium-sized cities, it has become one of the most important steps for the urban traffic strategy to solve the traffic problems. Since the urban traffic is a complex system in various factors and huge scale, to establish related mathematical model through computer numerical simulation is a significant solution to the comprehensive problems of complex analysis, decision and planning. At present researches on the problems have been achieved in many foreign countries, but domestic research is not enough, especially in the practical application. The macroscopic traffic flow model and microscopic traffic flow model are described and cellular automaton model, dual channel decision model and car-following model are analyzed in this paper, prediction of the ideal traffic flow and trip distribution is consequently concluded, which deepen the understanding to the traffic flow of various phenomenon intrinsic mechanism and predict most closely to the actual situation of traffic flow, which can make fundamental work for traffic flow simulation and for real-time traffic control[1-3].
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Grigoropoulos, Georgios, Seyed Abdollah Hosseini, Andreas Keler, Heather Kaths, Matthias Spangler, Fritz Busch, and Klaus Bogenberger. "Traffic Simulation Analysis of Bicycle Highways in Urban Areas." Sustainability 13, no. 3 (January 20, 2021): 1016. http://dx.doi.org/10.3390/su13031016.
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The ongoing increase of bicycle traffic in urban areas forces transport authorities to reconsider the space allocation for different transport modes. Transport policies favor the introduction of high-quality bicycle infrastructure along urban corridors to improve the traffic quality and safety for bicyclists but more importantly to increase the attractiveness of bicycling and over vehicular modes. Especially in urban areas with an already established high and steadily increasing share of bicyclists, the introduction of bicycle highways is considered to further alleviate saturated interurban public transport and motor vehicle connections and increase the average traveled distance by non-motorized modes. Due to the expensive implementation costs and the space restrictions in already built-up urban environments, there should be an extensive planning phase for defining the expected changes in traffic efficiency and safety. However, the effects of urban bicycle highways on traffic performance metrics of bicyclists as well as other road users are not thoroughly studied. This paper aims to quantify and assess the potential effects of urban bicycle highway on road users. The study considers a possible inner-city pilot route in the city of Munich, where the present bicycle infrastructure is planned to be upgraded to a bicycle highway. A simulation model is designed using traffic data from field observations and future estimates for the traffic composition. Through microscopic traffic simulation, the potential effects of the introduced infrastructure on road users are determined for different study scenarios. Results show that traffic quality thresholds for bicycle highways, as defined in official guidelines, can only be fulfilled through the implementation of special bicycle traffic control measures such as bicycle coordination or bicycle passage time extension. Finally, unidirectional bicycle highways together with bicycle passage time extension provided the best overall traffic performance for bicycle traffic and motor vehicle traffic.
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Hong, Rongrong, Huan Liu, Chengchuan An, Bing Wang, Zhenbo Lu, and Jingxin Xia. "An MFD Construction Method Considering Multi-Source Data Reliability for Urban Road Networks." Sustainability 14, no. 10 (May 19, 2022): 6188. http://dx.doi.org/10.3390/su14106188.
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Road network traffic management and control are the key mechanisms to alleviate urban traffic congestion. With this study, we aimed to characterize the traffic flow state of urban road networks using the Macroscopic Fundamental Diagram (MFD) to support area traffic control. The core property of an MFD is that the network flow is maximized when network traffic stays at an optimal accumulation state. The property can be used to optimize the temporal and spatial distribution of traffic flow with applications such as gating control. MFD construction is the basis of these MFD-based applications. Although many studies have been conducted to construct MFDs, few studies are dedicated to improving the accuracy considering the reliability of different sources of data. To this end, we propose an MFD construction method using multi-source data based on Dempster–Shafer evidence (DS evidence) theory considering the reliability of different data sources. First, the MFD was constructed using VTD and CSD, separately. Then, the fused MFD was derived by quantifying the reliability of different sources of data for each MFD parameter based on DS evidence theory. The results under real data and simulated data show that the accuracy of the constructed MFDs was greatly improved considering the reliability of different data sources (the maximum MFD estimation error was reduced by 22.3%). The proposed method has the potential to support the evaluation of traffic operations and the optimization of signal control schemes for urban traffic networks.